Religion and perceptions of community-based conservation in Ghana, West Africa
Bibliographic record
Abstract
Adapting community-based protected areas to local context and evaluating their success across a range of possible socio-economic and ecological outcomes depends, in part, on understanding the perceptions of local actors. This article presents results from a mixed methods study that focuses on how and why religious identity, a prominent aspect of Ghanaian culture, is related to perceptions of the performance of several Community Resource Management Areas (CREMAs). CREMAs are a form of Ghanaian protected area that emphasizes community participation and a range of socio-economic and ecological objectives. Using importance-satisfaction analysis, large-scale survey results show that respondents that identify as Christians consistently assign greater importance to CREMA outcomes than do those that identify with Traditional religions. Education and whether respondents were native to an area (both of which were correlated with religious identity) were also systematically related to perceptions of CREMA importance, with those that are educated and non-native to an area tending to assign higher importance to CREMA outcomes. Follow up focus group participants from the Avu Lagoon CREMA suggest that the patterns result from differing 'openness' to new ideas, relative dependence on natural resources, acceptance of Traditional practices associated with conservation, and a sense, for some, that ecological conditions are divinely ordained. Christianity, education and non-nativity are associated with much larger performance gaps, particularly with respect to socio-economic impacts. The article concludes with a discussion of the implications for conservation interventions and the use of perceptions in assessing protected area performance.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".